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Relative cerebral blood volume (rCBV) from dynamic susceptibility contrast (DSC)-MRI is a valuable biomarker in patients with glioblastoma for assessing treatment response and predicting overall survival. DSC-MRI based on echo planar images (EPI) may possess severe geometric distortions from magnetic field inhomogeneities up to the order of centimeters. The aim of this study is to assess how much two readily available EPI-based geometric distortion correction methods, FSL TOPUP and EPIC, affect rCBV values from DSC-MRI in patients with confirmed glioblastoma.

We used a combined single-shot 2D gradient-echo (T2*), spin-echo (T2) EPI sequence to estimate both T2* and T2-weighted rCBV from the same contrast agent injection. Effects of distortion correction on the positive phase-encoded T2- and T2*-images were assessed in healthy anatomical brain regions in terms of Wilcoxon signed rank tests on median rCBV change and on Dice coefficients, as well as in tumor lesions in terms of Wilcoxon signed rank tests on V values. Our findings may indicate that uncorrected rCBV values can be underestimated from positive phase-encoding EPI and that geometric distortion correction is warranted when comparing EPI-based data to conventional MRI.
Sarcomas are rare tumours of mesenchymal origin that are often treated with surgical resection and radiation to prevent local recurrence (LR). Surveillance for LR after surgical resection is often done with contrast-enhanced MRI, however, the optimal frequency of surveillance imaging is unknown. The aims of this study are to calculate LR growth, and to evaluate the factors that affect LR growth and to use this data to predict the optimal imaging surveillance frequency.

Retrospective cohort study of patients with sarcoma who were treated at a tertiary care academic institution between 01/01/2007 and 01/03/2020 identified 34 patients with 60 histologically confirmed LRs. The maximum LR length was measured on each surveillance MRI. Linear mixed-effects models were used to calculate the maximum LR length growth rate. Selpercatinib nmr We evaluated whether age, sex, primary sarcoma tumour size, sarcoma grade, margins, chemotherapy or radiation therapy affected the growth rate of the maximum LR length.

One patient had 6 LRs (2ely performed every 6 months when LRs are expected to be just less than 1.0 cm in length.
Patients with microscopically positive resection margins had LRs that grew faster than patients with negative margins. Surveillance imaging with contrast-enhanced MRI could be conservatively performed every 6 months when LRs are expected to be just less than 1.0 cm in length.
To investigate imaging findings of esophageal motility disorders on dynamic real-time.

102 patients with GERD-like symptoms were included in this retrospective study between 2015-2018. Dynamic real-time MRI visualized the transit of a 10 mL pineapple juice bolus through the esophagus and EGJ with a temporal resolution of 40 ms. Dynamic and anatomic parameters were measured by consensus reading. Imaging findings were compared to HRM utilizing the Chicago classification of esophageal motility disorders, v3.0.

All 102 patients completed real-time MRI in a median examination time of 15 min. On HRM, 14 patients presented with disorders with EGJ outlet obstruction (EGJOO) (13.7 %), 7 patients with major disorders of peristalsis (6.9 %), and 32 patients with minor disorders of peristalsis (31.4 %). HRM was normal in 49 patients (48.0 %). Incomplete bolus clearance was significantly more frequent in patients with esophageal motility disorders on HRM than in patients with normal HRM (p = 0.0002). In patients with motility disorders with EGJOO and major disorders of peristalsis, the esophageal diameter tended to be wider (23.6 ± 8.0 vs. 21.2 ± 3.5 mm, p = 0.089) and the sphincter length longer (19.7 ± 7.3 vs. 16.7 ± 3.0 mm, p = 0.091) compared to patients with normal HRM. 3/7 patients with achalasia type II were correctly identified by real-time MRI and one further achalasia type II patient was diagnosed with a motility disorder on MRI films. The other 3/7 patients presented no specific imaging features.

Real-time MRI is an auxiliary diagnostic tool for the assessment of swallowing events. Imaging parameters may assist in the detection of esophageal motility disorders.
Real-time MRI is an auxiliary diagnostic tool for the assessment of swallowing events. Imaging parameters may assist in the detection of esophageal motility disorders.
To investigate whether combined texture analysis and machine learning can distinguish malignant from benign suspicious mammographic calcifications, to find an exploratory rule-out criterion to potentially avoid unnecessary benign biopsies.

Magnification views of 235 patients which underwent vacuum-assisted biopsy of suspicious calcifications (BI-RADS 4) during a two-year period were retrospectively analyzed using the texture analysis tool MaZda (Version 4.6). Microcalcifications were manually segmented and analyzed by two readers, resulting in 249 image features from gray-value histogram, gray-level co-occurrence and run-length matrices. After feature reduction with principal component analysis (PCA), a multilayer perceptron (MLP) artificial neural network was trained using histological results as the reference standard. For training and testing of this model, the dataset was split into 70 % and 30 %. ROC analysis was used to calculate diagnostic performance indices.

226 patients (150 benign, 76 malignant) were included in the final analysis due to missing data in 9 cases. Feature selection yielded nine image features for MLP training. Area under the ROC-curve in the testing dataset (n = 54) was 0.82 (95 %-CI 0.70-0.94) and 0.832 (95 %-CI 0.72-0.94) for both readers, respectively. A high sensitivity threshold criterion was identified in the training dataset and successfully applied to the testing dataset, demonstrating the potential to avoid 37.1-45.7 % of unnecessary biopsies at the cost of one false-negative for each reader.

Combined texture analysis and machine learning could be used for risk stratification in suspicious mammographic calcifications. At low costs in terms of false-negatives, unnecessary biopsies could be avoided.
Combined texture analysis and machine learning could be used for risk stratification in suspicious mammographic calcifications. At low costs in terms of false-negatives, unnecessary biopsies could be avoided.
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